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Record W3152537902 · doi:10.24908/iqurcp.14687

Changes in Knowledge Across Time

2021· article· en· W3152537902 on OpenAlexaffvenue
Kenda Parsons, Vivian Rigg, Della Boudreau, Ellen Doucet, Lily Toutounji, Lojain Hamwi, Deepthi Kamawar

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2021
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsIgnoranceMetacognitionPsychologyTask (project management)CognitionCognitive psychologyRelation (database)Knowledge levelProcess (computing)Developmental psychologyMathematics educationComputer scienceEpistemology

Abstract

fetched live from OpenAlex

Our study focuses on children’s understanding of their own knowledge and how it changes over time. Preschool-aged children perform above chance when asked about current knowledge, but only children older than 5 years of age performed above chance for past, future, or intraindividual knowledge (Atance & Caza, 2018; Caza et al., 2016). However, we do not currently know whether awareness of past and future knowledge is related. While this type of awareness seems conceptually related to metacognition (the awareness of one’s own ignorance or knowledge; Rohwer et al., 2012), the relation to this skill is unknown. Thus, the goal of the current study is to investigate how children’s awareness of their own epistemic knowledge is related to their metacognitive abilities. This study will explore children between the ages of 3.5- through 5-years-old, who will be assessed on their understanding of their current, past, and future knowledge, as well as other tasks assessing metacognitive skills. Further, we will explore the role of theory of mind and inhibitory control. We predict that children who do well on the epistemic knowledge task for the past will display better performance on the task asking about the future, and that both will be related to the other cognitive skills measured. Due to the current global situation, we converted our study materials to an online format. Our poster will highlight this process and discuss ways to approach challenges in online developmental testing. Though data collection is ongoing, we present initial insight into the process, drawbacks, and benefits of online testing. Keywords: Epistemic Knowledge, Metacognition, Theory of Mind, Child Development References Atance, C. M., & Caza, J. S. (2018). “Will I know more in the future than I know now?” Preschoolers’ judgments about changes in general knowledge. Developmental Psychology, 54(5), 857–865. http://dx.doi.org.proxy.library.carleton.ca/10.1037/dev0000480 Caza, J. S., Atance, C. M., & Bernstein, D. M. (2016). Older (but not younger) preschoolers understand that knowledge differs between people and across time. British Journal of Developmental Psychology, 34(3), 313–324. https://doi.org/10.1111/bjdp.12130 Rohwer, M., Kloo, D., & Perner, J. (2012). Escape from metaignorance: How children develop an understanding of their own lack of knowledge. Child Development, 83(6), 1869–1883. https://doi.org/10.1111/j.1467-8624.2012.01830.x

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.205
GPT teacher head0.473
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes2
Has abstractyes

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